Abstract: A failure prediction method and device for a storage device are provided. The method comprises: inputting SMART data of the storage device obtained in real time into each of a plurality of base classification models to obtain a classification result for the SMART data of the storage device obtained in real time that is output by the each classification model, wherein the each base classification model is obtained by training using historical SMART data of a plurality of storage devices and/or SMART data of the plurality of storage devices obtained online; determining whether the SMART data of the storage device obtained in real time is healthy data or erroneous data, based on classification results of the plurality of base classification models; predicting whether the storage device will fail, based on a number of SMART data that is determined as healthy data and a number of SMART data that is determined as erroneous data among SMART data of the storage device obtained within a predetermined time window.

Abstract: Computerized methods and systems for the analysis of textual data, including: receiving, from one or more memories at one or more processors, textual data; using the processors, formatting the textual data for analysis and applying a probabilistic topic model to the textual data to extract semantically meaningful topics that collectively describe it; using a keyword weighting module, generating a topic cloud view representing the topics as a tagcloud with each being associated with a plurality of keywords; using a topic ordering module, generating a document distribution view representing a distribution of the textual data across multiple topics; using a document entropy calculation module, generating a document scatterplot view representing how many topics are attributable to the textual data; using a temporal topic trend calculation module, generating a temporal view representing changes in the occurrence of topics over time; and displaying one or more of the views to a user.